You can directly import data from Intercom to Treasure Data.
- Basic knowledge of Treasure Data, including the TD Toolbelt
- Basic knowledge of Intercom
Go to Integrations Hub > Catalog and search and select Intercom.
Select Create. You are creating an authenticated connection.
The following dialog opens.
Access to Intercom requires OAuth2 authentication.
Select Click here to connect to your Intercom account.
Enter your credentials to sign into Intercom.
After you grant access to Treasure Data you are redirected back to TD Console. Choose the Intercom connector again, then choose the OAuth Authenticate method. You will see an OAuth connection with your account name in the dropdown list. Choose the account you want to use and then proceed to create the connection.
Name your new Google Drive Connection. Select Done.
Previously for this data connector, App id and API Key was used for authentication. However, Intercom started their OAuth flow and Intercom API keys were deprecated.
If you are using Google Sign-In to log into Intercom, make sure that you are already logged in Intercom before starting the OAuth flow. Intercom requires password logins, not Google Sign-In, through the OAuth flow.
Initiate the OAuth flow as you did previously, even if you have been using API keys. OAuth is prioritized over API keys, if both are specified.
After creating the authenticated connection, you are automatically taken to the Authentications tab. Look for the connection you created and select New Source.
From Source select users or conversations.
Parameters:
- Incremental: Use when importing data based on a schedule. Use to import only the newest user or conversation created since the last run.
From Source choose tags or segments
You can see a preview of your data before running the import by selecting Generate Preview. Data preview is optional and you can safely skip to the next page of the dialog if you choose to.
- Select Next. The Data Preview page opens.
- If you want to preview your data, select Generate Preview.
- Verify the data.
For data placement, select the target database and table where you want your data placed and indicate how often the import should run.
Select Next. Under Storage, you will create a new or select an existing database and create a new or select an existing table for where you want to place the imported data.
Select a Database > Select an existing or Create New Database.
Optionally, type a database name.
Select a Table> Select an existing or Create New Table.
Optionally, type a table name.
Choose the method for importing the data.
- Append (default)-Data import results are appended to the table. If the table does not exist, it will be created.
- Always Replace-Replaces the entire content of an existing table with the result output of the query. If the table does not exist, a new table is created.
- Replace on New Data-Only replace the entire content of an existing table with the result output when there is new data.
Select the Timestamp-based Partition Key column. If you want to set a different partition key seed than the default key, you can specify the long or timestamp column as the partitioning time. As a default time column, it uses upload_time with the add_time filter.
Select the Timezone for your data storage.
Under Schedule, you can choose when and how often you want to run this query.
- Select Off.
- Select Scheduling Timezone.
- Select Create & Run Now.
- Select On.
- Select the Schedule. The UI provides these four options: @hourly, @daily and @monthly or custom cron.
- You can also select Delay Transfer and add a delay of execution time.
- Select Scheduling Timezone.
- Select Create & Run Now.
After your transfer has run, you can see the results of your transfer in Data Workbench > Databases.
Name your Transfer and select Done to start.
You can install the newest TD Toolbelt.
$ td --version
0.15.0Prepare configuration file (for eg: load.yml) as shown in the following example, with your Intercom account access information to:
import Users
in:
type: intercom
access_token: xxxxxxx
target: users
incremental: false
out:
mode: appendimport Conversations
in:
type: intercom
access_token: xxxxxxx
target: conversations
incremental: false
out:
mode: appendimport Segments
in:
type: intercom
access_token: xxxxxxx
target: segments
out:
mode: appendimport Tags
in:
type: intercom
access_token: xxxxxxx
target: tags
out:
mode: appendThe preceding example dumps Intercom’s users objects. Here access_token is a valid access token achieved from Intercom. Using the OAuth flow through TD Console is recommended. Your Personal Access Token can be used for access_token instead of the OAuth flow.
You can select which data needs to be fetched from store as target option.
You can preview data to be imported using the command td connector:preview.
$ td connector:preview load.yml
+-----------+--------------+----------------------------+----
| id:string | user_id:string | email:string | ...
+-----------+----------------+-------------------------------
| "1" | "33" | "xxxx@xxx.com" |
| "2" | "34" | "yyyy@yyy.com" |
| "3" | "35" | "zzzz@zzz.com" |
| "4" | "36" | "aaaa@aaa.com" |
| "6" | "37" | "bbbb@bbb.com" |
+-----------+----------------+--------------------------+----Submit the load job. It may take a couple of hours depending on the data size. Users need to specify the database and table where their data are stored.
It is recommended to specify --time-column option, since Treasure Data’s storage is partitioned by time. If the option is not given, the Data Connector will choose the first long or timestamp column as the partitioning time. The type of the column specified by --time-column must be either of long and timestamp type.
If your data doesn’t have a time column you may add it using add_time filter option. More details at add_time filter plugin
$ td connector:issue load.yml --database td_sample_db --table td_sample_table --time-column created_atThe preceding command assumes you have already created database(td_sample_db) and table(td_sample_table). If the database or the table do not exist in TD this command will not succeed, so create the database and table manually or use --auto-create-table option with td connector:issue command to auto-create the database and table:
$ td connector:issue load.yml --database td_sample_db --table td_sample_table --time-column created_at --auto-create-tableYou can assign Time Format column to the "Partitioning Key" by "--time-column" option.
You can schedule a periodic Data Connector execution for periodic Intercom import. We configure our scheduler carefully to ensure high availability. By using this feature, you no longer need a cron daemon on your local data center.
A new schedule can be created using the td connector:create command. The name of the schedule, cron-style schedule, the database and table where their data will be stored, and the Data Connector configuration file are required.
$ td connector:create \
daily_intercom_import \
"10 0 * * *" \
td_sample_db \
td_sample_table \
load.ymlThe cron parameter also accepts these three options: @hourly, @daily and @monthly. | By default, schedule is setup in UTC timezone. You can set the schedule in a timezone using -t or --timezone option. The --timezone option only supports extended timezone formats like 'Asia/Tokyo', 'America/Los_Angeles' etc. Timezone abbreviations like PST, CST are *not* supported and may lead to unexpected schedules.
You can see the list of scheduled entries by td connector:list.
$ td connector:listtd connector:show shows the execution setting of a schedule entry.
td connector:show daily_intercom_importtd connector:history shows the execution history of a schedule entry. To investigate the results of each individual execution, use td job jobid.
td connector:history daily_intercom_importtd connector:delete will remove the schedule.
td connector:delete daily_intercom_import